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Published Ahead of Print on June 8, 2017, as doi:10.3324/haematol.2017.169680.
Copyright 2017 Ferrata Storti Foundation.
Hemoglobin concentration, total hemoglobin mass and plasma
volume in patients: implications for anemia
by James M. Otto, James O. M. Plumb, Eleri Clissold, Shriya Kumar, Denis J. Wakeham,
Walter Schmidt, Michael P.W. Grocott, Toby Richards, and Hugh Montgomery
Haematologica 2017 [Epub ahead of print]
Citation: Otto JM, Plumb JOM, Clissold E, Kumar S, Wakeham DJ, Schmidt W, Grocott MPW,
Richards T, and Montgomery H. Hemoglobin concentration, total hemoglobin mass and plasma volume
in patients: implications for anemia. Haematologica. 2017; 102:xxx
doi:10.3324/haematol.2017.169680
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Hemoglobin concentration, total hemoglobin mass and
plasma volume in patients: implications for anemia
James M Otto1, James OM Plumb2,3,4, Eleri Clissold2,3,4, Shriya Kumar2,3,4, Denis
J Wakeham5, Walter Schmidt6; Michael PW Grocott2,3,4, Toby Richards1 and
Hugh E Montgomery7
1
Division of Surgery and Interventional Science, University College London,
London, UK
2
Anaesthesia and Critical Care Research Unit, University Hospital Southampton
NHS Foundation Trust, Southampton, UK
3
Integrative Physiology and Critical Illness Group, Clinical and Experimental
Sciences, Faculty of Medicine, University of Southampton, University Road,
Southampton, UK;
4
Critical Care Research Area, Southampton NIHR Respiratory Biomedical
Research Unit, Southampton, UK
5
School of Sport, Physiology and Health Group, Cardiff Metropolitan University,
Cardiff, UK
6
Department of Sports Medicine/Sports Physiology, University of Bayreuth,
Bayreuth, Germany
7
Centre for Human Health and Performance/ Institute for Sport, Exercise and
Health, University College London, and NIHR University College London
Hospitals Biomedical Research Centre, London, UK.
Details of authors’ contributions
H.E.M., T.R., M.G., and J.O. conceived the study. J.O., J.O.M.P., E.C., S.K., and
D.W. assisted with data collection, with J.O. performing all statistical analyses.
H.E.M., J.O. & J.O.M.P drafted the manuscript, to which T.R., M.G., W.S. then
contributed. All authors read and approved the final version of the manuscript.
Running heads
[Hb], tHb-mass and PV in anemia
Corresponding author
Dr James Otto PhD
Email: [email protected]
Word Count
Abstract: 254 words
Main text: 4221
Tables: 2
Figures: 6
Supplemental files: 1
Trial registration
Not applicable
Acknowledgements
1
The authors would like to thank Siemen’s for supplying the RAPIDPoint 500
blood gas machine and associated consumables used during this study at the
Southampton General Hospital.
In addition, we would like to thank
the NIHR/Wellcome Clinical Research Facility for allowing patients to be tested
in this facility at University College London Hospital. HM is funded in part by
the NIHR University College London Hospitals Biomedical Research Centre, to
whom we express our thanks. MG is funded in part by the NIHR Southampton
Respiratory Biomedical Research Unit. Finally, we would like to Dr Nadine
Wachsmuth for her assistance in training JO and JOMP in the optimized carbon
monoxide rebreathing method at the Department of Sports Medicine/Sports
Physiology, University of Bayreuth, Germany.
2
Abstract
In practice, clinicians generally consider anemia (circulating hemoglobin
concentration < 120 g.l-1 in non-pregnant females and < 130 g.l-1 in males) as due
to impaired hemoglobin synthesis or increased erythrocyte loss or destruction.
Rarely is a rise in plasma volume relative to circulating total hemoglobin mass
considered as a cause. But does this matter? We explored this issue in patients,
using the optimized carbon-monoxide rebreathing method to measure
hemoglobin concentration and thereby calculate plasma volume in healthy
volunteers, surgical patients, and those with inflammatory bowel disease, chronic
liver disease or heart failure.
We studied 109 participants.
Hemoglobin mass correlated well with its
concentration in the healthy, surgical and inflammatory bowel disease groups (r=
0.687-0.871, p< 0.001). However, they were poorly related in liver disease (r=
0.410, p= 0.11) and heart failure patients (r= 0.312, p= 0.16). Here, hemoglobin
mass explained little of the variance in its concentration (adjusted R2= 0.109 and
0.052; p= 0.11 and 0.16), whilst plasma volume did (R2 change 0.724 and 0.805
in heart and liver disease respectively, p<0.0001). Exemplar patients with
identical (normal or raised) total hemoglobin masses were diagnosed as
profoundly anemic (or not) depending on differences in plasma volume that had
not been measured or even considered as a cause. The traditional inference that
anemia generally reflects hemoglobin deficiency may be misleading, potentially
resulting in inappropriate tests and therapeutic interventions to address
‘hemoglobin deficiency’ not ‘plasma volume excess’. Measurement of total
hemoglobin mass and plasma volume is now simple, cheap and safe, and its more
routine use advocated.
3
Introduction
Anemia is defined as a reduction in the circulating concentration of hemoglobin
([Hb]) to < 120 g.l-1 in non-pregnant females and < 130 g.l-1 in males.1
Such reductions can result from the destruction or loss of erythrocytes or a failure
of their production, or from impaired hemoglobin synthesis. Given its diverse
etiology, anemia is common, affecting over 1.6 billion people worldwide 2, and is
associated with impaired functional capacity, reduced quality of life 3, and poorer
outcome in diverse disease states. 4-9
For all these reasons, circulating hemoglobin concentrations are routinely
measured in clinical practice. Once anemia is identified, the cause of impaired
hemoglobin synthesis or erythrocytosis, or of increased red cell loss or
destruction, is often sought and treatment (either of the underlying cause, or
through the administration of packed donor red cells) initiated.
However, it is now becoming clear that this approach may be somewhat
simplistic. The concentration of circulating hemoglobin will depend not just on
the total circulating quantity of hemoglobin
(total hemoglobin mass, (tHb-
mass)), but also on the volume of plasma (plasma volume, PV) in which it is
suspended. These factors are not routinely considered separately, or measured, in
clinical practice and even in experienced hands their estimation is not trivial.
However, such assessment may be important if the drivers of an altered [Hb]- and
the appropriate therapeutic response- are to be truly understood. Thus, the
circulating hemoglobin concentration in athletes matches that in sedentary
individuals, meaning that a contribution of increased red cell oxygen carriage to
4
elite performance was largely dismissed. Then, in 2001, Heinicke and colleagues
demonstrated that tHb-mass was increased by some 35% in elite endurance
athletes, [Hb] matching that in the untrained only because PV was expanded to a
similar degree. 10
Likewise, alterations in the relationship between plasma volume and tHb-mass
might strongly influence [Hb] in disease states. Anemia is common in diseases
such as cancer
11
, inflammatory bowel disease (IBD)
(CHF) 8, chronic kidney disease (CKD)
13
12
, chronic heart failure
and chronic liver disease (CLD).
14
Traditionally, this has been considered the result of a reduced tHb-mass. But a
low [Hb] might also be found when hemoglobin synthesis, erythrocytosis and
tHb-mass are all entirely normal (or even high), if plasma volume is
disproportionately expanded. This can occur through disease-related changes in
global water balance or distribution of body water. Thus, patients with
inflammatory bowel disease might face enteric blood loss, suppressed
hemoglobin synthesis or anemia of chronic inflammation; CLD patients may
likewise lose blood, have an expanded circulating plasma volume due to
hyperaldosteronism, or face fluid shifts as a result of raised portal venous
pressure or hypoalbuminemia; and patients with chronic heart failure may suffer
an increase in circulating volume due to factors including increased reninangiotensin-aldosterone axis activity. 15 In contrast, contractions in PV caused by
pharmacotherapy may mask a fall in tHb-mass by maintaining [Hb]. 16
The extent to which this is true has not been addressed, largely due to historical
methodological limitations: circulating red cell volume (RCV, ml) or plasma
5
volume has generally have been determined through radiolabelling of red blood
cells or albumin respectively.
17
Such techniques are costly and time consuming,
and not without risk, and are thus not routinely deployed unless in special
circumstances (this method is recommended for disease diagnosis by the
Polycythemia Rubra Vera Study Group). 18
Such barriers may be overcome through the use of an ‘optimized carbon
monoxide (CO) rebreathing’ (oCOR) method
19
: inhaled CO binds avidly to
circulating hemoglobin, and the concentration of the resultant COHb complex
can be readily measured. Knowing the quantity of absorbed CO, tHb-mass can be
measured and, knowing [Hb], PV calculated. The method is cheap, simple and
safe to use- but has only rarely been applied in the clinical setting.
Thus, the relative contributions of PV and tHb-mass to measured [Hb] across
disease states have not been described. We sought to address this issue.
6
Methods
This was a prospective, observational clinical study. We studied five groups:
healthy volunteers (HV), preoperative patients awaiting major surgery and those
suffering inflammatory bowel disease (IBD), as well as patients in whom
alterations in plasma volume might more commonly occur (those with chronic
liver disease, CLD) or chronic heart failure (CHF)). Each participant was studied
on one occasion between February 2015 and May 2016.
Optimized Carbon Monoxide Rebreathing Method (oCOR)
The use of CO to determine tHb-mass was first proposed in the late 1800s, with
refined techniques being published 100 years later.
20
In 2005, Schmidt and
Prommer reported a simpler and faster technique (described in detail below)
which also required less blood sampling.
19
It was applied almost exclusively,
however, in the fields of athletic physiology, and thus failed to come to the
attention of the bulk of the broader clinical/medical community.
tHb-mass was determined using the validated oCOR method described in detail
by Schmidt and Prommer.
19
In brief, COHb concentration in blood was
measured before and after 2-min rebreathing a known CO volume (0.5 to 1.0
ml.kg-1 in this study depending on gender). Each participant was seated for 15
minutes to allow stabilization of plasma volume, after which a mouthpiece
connected them via a container of ‘soda lime’~10g (carbon dioxide scrubber) to
a spirometer (Spico-CO Respirations-Applikator, Blood Tec, Germany) and a 3
liter anaesthetic bag pre-filled with 100% oxygen. The patient exhaled to residual
volume, breathed in the CO dose via the spirometer, held their breath for 10 s,
7
then continued normal breathing into the closed circuit via the spirometer for 1
min 50s. The participant then exhaled to residual volume, this exhaled volume
being collected and analyzed to quantify the CO not absorbed into the
bloodstream. Disconnected from the mouthpiece, participants finally fully
exhaled to residual volume into a CO gas analyzer (Draሷ ger Pac 7000,
Draሷ egerwerk AG & Co. KGaA, Germany) before and at minutes 4 after CO
rebreathing, to determine the CO concentration exhaled after disconnecting the
patient from the spirometer that will also have not been adsorbed into the blood.
Statistical Analysis
Statistical analysis was performed using SPSS Statistics (Version 23.0 for Apple
Macintosh, Chicago, IL, USA). Values are presented as mean ± standard
deviation (SD), unless otherwise stated. Median and interquartile range (IQR)
are reported when variables were not normally distributed. Categorical variables
are presented as frequency (%). Pearson’s correlation coefficient assessed the
relationship between [Hb] and tHb-mass, allowing adjustment for PV (ml).
Linear regression assessed the proportion of variance in tHb-mass explained by
[Hb], allowing adjustment for PV (ml). In both correlation and regression
analyses [Hb] and tHb-mass are expressed in g.l-1 and grams, respectively and PV
in ml. This is also the case elsewhere, unless otherwise stated.
Differences across sub-groups were assessed by one-way analysis of variance
(ANOVA), prior to which the assumption of normality was tested by the
8
Levene’s test for homogeneity of variances. Where homogeneity of variance was
verified, being the case for [Hb], Hct, tHb-mass (g), PV (%) and weight, a oneway ANOVA was performed, with post hoc comparisons by Gabriel’s test due to
the slightly different sample sizes across sub-groups. When homogeneity of
variance was violated, as was the case for PV (ml & ml.kg-1), age and tHb-mass
(g.kg-1), a Welch ANOVA
21
was used with post hoc comparisons made by the
Games-Howell test, as this does not rely on the assumption of equal variances. 22
All tests were two-sided with statistical significance being accepted as a p-value
of < 0.05.
Power calculation
The power calculation was based on the study by Hinrichs and colleagues
was performed using G*3 Power version 3.1.9.2.
24
23
and
According to Hinrichs and
colleagues, the relationship (expressed as Pearson’s correlation coefficient)
between [Hb] and tHb-mass was r= 0.59, p< 0.05. Based on this, using a twotailed correlation: bivariate normal model, we calculated that 21 patients would
provide 80% power at the 5% significance level to detect a correlation of at least
r= 0.59 between [Hb] and tHb-mass. Given that five groups were studied, a total
of 105 participants were required.
Ethical approval
Ethical approval was granted by the London- Camden and Kings Cross Research
Ethics Committee (REC reference: 13/LO/1902). Written informed consent was
obtained from all participants.
9
Results
One hundred and nine patients (61% male: mean (IQR) age 52 (36-64) years)
consented to take part in the study.
Supplementary Figure 1 shows a
Consolidated Standards of Reporting Trials (CONSORT) flow diagram indicating
included and excluded patients and sub-groups. Sixteen patients were tested at
Southampton General Hospital, ninety at UCLH (including HV) and three at the
Royal Free Hospital (RFH). Surgical specialties are shown in Supplementary
Table S1 online with patient characteristics and etiology of disease for IBD
patients in Supplementary Table S2. Patient characteristics, medications and
etiology of CLD and CHF are shown in Supplementary Table S3 and Table S4
online, respectively. There were no differences in weight between sub-groups.
Healthy volunteers (n= 21) were younger compared to all patient groups (p<
0.0001) with CHF patients (n= 22) being older than IBD (n= 21, p= 0.001),
surgical (n= 28, p= 0.008) and CLD patients (n= 16, p= 0.002). Figure 1 A-D
shows hematological variables and Figure 2 A-B plasma volumes across different
sub-groups.
Hemoglobin concentration
Hemoglobin concentration was 128.4 ± 18.1 g.l-1 in the subjects overall. Across
sub-groups, CLD patients had lower [Hb] when compared to HV and other
disease groups (p< 0.0001, Figure 1B). Anemia prevalence (n=34 [39%]) varied
across disease sub-groups (CLD 15 [94%], CHF 12 [55%], IBD 2 [9%], surgical
5 [18%]). Amongst healthy volunteers, 5 (24%, all female) were anemic.
10
Total hemoglobin mass
Mean ± SD tHb-mass was 669 ± 181 grams (8.5 ±1.9 g.kg-1 body mass) in
subjects overall, with no statistically significant differences across sub-groups
(Figure 1, C, D). tHb-mass was higher in males than females: (758 ± 152 vs. 533
± 132 g, p< 0.0001; and 8.9 ± 1.8 vs. 7.9 ± 2.0 g.kg-1, p= 0.006, respectively).
Plasma volume
Mean ± SD plasma volume was 3667 ± 1020 ml (47.1 ± 11.3 ml.kg-1) in subjects
overall. PV was higher in males than females (4040 ± 1038 vs. 3093 ± 672 ml
respectively, p< 0.0001), but not when weight adjusted (47.6 ± 11.3 vs. 46.2 ±
11.5 ml.kg-1, p= 0.556). It also differed across disease groups, being expanded
and more varied in CLD (4965 ± 1447 ml) compared to HV (3429 ± 538 ml, p=
0.006), IBD (3202 ± 653 ml, p= 0.002) and surgical patients (3297 ± 590 ml, p=
0.003), but not CHF (3883 ± 953 ml, p= 0.100). Adjusted for body weight, PV
was similarly expanded in CLD (59.1 ± 16.0 ml.kg-1) when compared to IBD
(42.5 ± 8.3 ml.kg-1, p= 0.008) and surgical patients (41.3 ± 7.8 ml.kg-1, p= 0.004),
but again was similar to that in CHF patients (48.6 ± 9.2 ml.kg- 1, p= 0.172) or
HV (49.1 ± 7.9 ml.kg- 1, p= 0.191).
Hemoglobin concentration was influenced by the degree of PV expansion (Figure
4A), being lower in patients with severe PV expansion (n= 46, 119.0 ± 17.7 g.l-1)
than mild to moderate PV expansion (n= 36, 131.1 ± 13.8 g.l-1, p= 0.005), and
normal PV (n= 24, 140.7 ± 15.5 g.l-1, p< 0.0001), but not PV contraction (n= 3,
143.8 ± 11.8 g.l-1, p= 0.139)
11
Relationships between hemoglobin concentration and total hemoglobin mass
In the study cohort as a whole, [Hb] (g.l-1) correlated with tHb-mass (g) (r= 0.500,
p< 0.0001, n= 109), this being true in both males (r= 0.452, p< 0.0001) and
females (r= 0.462, p< 0.0001). Whilst true in HV and in IBD and surgical
patients (r= 0.871, p< 0.0001; r= 0.687, p< 0.0001; and r= 0.763, p< 0.0001
respectively; Figure 3 A-E) this was not the case in patients with CLD or CHF
(r= 0.410, p= 0.114 and r= 0.312, p= 0.157, respectively).
Whilst consistently statistically significant, the strength of the relationship
between [Hb] and tHb-mass weakened as plasma volume rose, r-values falling
from 0.94 to 0.91, 0.86 and 0.57 for those with low (n=3), normal (n=24), mildmoderately expanded (n=36) and severely expanded (n= 46) plasma volumes
respectively (p= 0.216 for the 3 with low PV, and p<0.0001 for the others). Subgroup analysis is hampered by small numbers, but data are presented in
Supplementary Table S5 online for completeness.
Total hemoglobin mass, plasma volume and hemoglobin concentration on an
individual level
The data presented thus suggest that, at an individual level, [Hb] was not a good
guide to tHb-mass- being strongly influenced by PV. This is illustrated in Figure
5 A-E, which shows data from individual participants ranked by weight-adjusted
tHb-mass from smallest to largest with corresponding PV (ml.kg-1) and [Hb] (g.l1
) in HV (A), IBD (B), surgical (C), CLD (D) and CHF (E) patients, respectively.
These show that patients who share a very similar tHb-mass may exhibit
12
markedly different [Hb] due to differences in PV. For example, in patients with
IBD (Figure 5B), patient numbers 17 and 18 have a very similar tHb-mass (9.2
g.kg-1 and 9.3 g.kg-1, respectively), yet one is defined as having a high normal
[Hb] (161 g.l-1) and the other as being anemic ([Hb] 107 g.l-1), due to substantial
differences in PV (37.2 ml.kg-1vs 65.7 ml.kg-1).
Similarly, in CLD patients
(Figure 5E), tHb-mass in patient numbers 2 and 3 are the same (5.2 g.kg-1) but the
first is considered to have a normal [Hb] (110 g.l-1), but the second to be
markedly anemic ([Hb] 69 g.l-1) due to a relatively raised PV in the latter (36.5
vs. 67.8 ml.kg-1 respectively).
Linear regression models
In the whole population, tHb-mass explained 25.0% of the variance in [Hb]
(adjusted R2 = 0.250, p< 0.0001). However, tHb-mass explained different
amounts of the variance in [Hb] across patient groups, adjusted R2 for HV,
surgical and IBD patients being 0.746, 0.565 and 0.446 respectively (p< 0.0001
in all cases). Of particular note, tHb-mass did not significantly explain variance in
[Hb] in the two patient groups most likely to suffer expanded plasma volume and
shifts in fluid- CLD (adjusted R2= 0.109, p= 0.114) or CHF patients (adjusted
R2= 0.052, p= 0.157). In keeping, PV independently accounted for a greater
proportion of the variance in [Hb] in these groups (R2 change 0.724 in CHF and
0.805 in CLD) than in HV (0.192), surgical patients (0.374) or IBD patients
(0.479) (p<0.0001 in all cases).
13
Hematological variables by anemia status
In the 39 anemic subjects (mean ± SD [Hb] 109.6 ± 12.5 g.l-1), when compared to
the 70 non-anemic ([Hb] 138.9 ± 10.6 g.l-1), tHb-mass (g & g.kg-1) was
significantly lower (594 ± 192 vs. 711 ± 162 g, p= 0.001; 7.7 ± 1.9 vs. 9.0 ± 1.8
g.kg-1, p= 0.001). However, PV (ml, and ml.kg-1) was also significantly higher in
anemic subjects (4083 ± 1351 vs. 3434 ± 686 ml, p= 0.007; 52.6 ± 12.2 vs. 44.0 ±
9.6 ml.kg-1, p< 0.0001: (see Table 1).
14
Discussion
We have studied the contribution of changes in circulating hemoglobin and
plasma volume to differences in the concentration of circulating hemoglobin. We
have done so in healthy volunteers and across a variety of disease states, selected
to be more or less likely to influence intravascular fluid status. By doing so, we
have shown that (i) variation in plasma volume contributes significantly to
variation in hemoglobin concentration, (ii) this contribution is greater in cases of
chronic liver disease of heart failure- diseases in which changes in total body
water and in its distribution are more likely to occur, and (iii) perhaps most
importantly, this may lead to some individuals being diagnosed as anemic whilst
having a tHb-mass which is normal or even supra-normal. These findings are of
direct clinical relevance. A basic medical education teaches that plasma volume
may be expanded in some disease states. But it is rarely if ever mentioned that
this might lead to hemodilution of such degree as to cause anemia. Thus, a
diagnosis of anemia generally leads to investigation of a cause for reduced
hemoglobin synthesis or increase erythrocyte destruction or loss. When such
features are not identified, a diagnosis of ‘anemia of chronic disease’ is likely
made. Rarely if ever is hemodilution considered as a cause, and measurement of
tHb-mass or plasma volume performed. This is exemplified by the fact that no
such measurements had been performed electively in the patients we studied.
Such deficits in consideration or action may in part relate to the difficulty and
expense of measuring such variables through traditional methods (radiolabelling
of red blood cells, for instance).
15
Thus, tHb-mass was generally strongly related to [Hb] (r ≥0.687 and p <0.0001
in all cases); tHb-mass explained a good deal of the variance in [Hb] (adjusted R2
in HV, surgical and IBD patients being 0.746, 0.565 and 0.446 respectively, p<
0.0001 in all cases); and PV independently accounted for only a small proportion
of the variance in [Hb] over that due to tHb-mass (R2 change 0.192, 0.374) or
0.479 in HV, surgical and IBD patients respectively). By contrast, in the two
patient groups most likely to suffer expanded plasma volume (CLD and CHF),
tHb-mass did not correlate with [Hb] (r= 0.410, p= 0.114; r= 0.312, p= 0.157,
respectively). Likewise, tHb-mass did not significantly explain variance in [Hb]
(adjusted R2= 0.109, p= 0.114; adjusted R2= 0.052, p= 0.157, respectively),
whilst PV independently accounted for a greater proportion of the variance in
[Hb] over and above tHb-mass in these groups (R2 change 0.724 in CHF and
0.805 in CLD). Thus, [Hb] is strongly influenced by disease-related changes in
PV. The relationship between [Hb] and tHb-mass weakened as plasma volume
rose (r-values falling from 0.94 and 0.91 in those with low or normal PV, to 0.57
amongst those in whom PV was severely expanded.
As a consequence, even amongst those in our small sample, we identified patients
with identical and normal tHb-mass, in some of whom severe anemia would be
diagnosed, likely triggering investigations focused upon failed erythrogenesis or
increased red cell destruction. As specific exemplars of the phenomenon, two
IBD patients had similar tHb-masses (9.2 and 9.3 g.kg-1), one having a high
normal [Hb] (161 g.l-1) and the other being anemic ([Hb] 107 g.l-1), due to
substantial differences in PV (37.2 ml.kg-1 vs. 65.7 ml.kg-1). Similarly, two CLD
16
patients had the same tHb-mass (5.2 g.kg-1), one having a normal [Hb] (110 g.l-1),
but the second being markedly anemic ([Hb] 69 g.l-1) due to a relatively raised PV
in the latter (36.5 vs. 67.8 ml.kg-1 respectively).
Our findings are thus of real clinical importance, as a significantly low [Hb] can
trigger a raft of (unwarranted) investigations (such as the assay of circulating
hematinic factors) or treatments (such as the administration of packed red blood
cells), whilst denying the administration of agents to reduce plasma volume,
which might sometimes be required. Blood transfusion itself carries risks
25
as
well as a price in terms of healthcare costs. Meanwhile, in other circumstances,
contraction in plasma volume might offer false reassurance by maintaining [Hb],
when tHb-mass is low.
Whilst tHb-mass is generally used as an index of oxygen carrying capacity and of
circulating red cell mass, others have previously reported total circulating red
blood cell volume (RCV) in this regard. In hematologically normal control
subjects, hematocrit (Hct) in the 20-50% range reportedly correlated well with
RCV (determined by
51
Cr labeling of RBCs: r= 0.880, p< 0.001).
26
However,
this relationship was disturbed when Hct fell outside this range, owing to wider
variability in PV. Such data support those from other radiolabelling studies in
suggesting that direct measurement of RCV (rather than the use of [Hb] or Hct) is
required for the accurate diagnosis of polycythemia.
27
Likewise, data derived
from the same technique which we applied (oCOR) show PV to be expanded
(variably, but along with increased RCV) in polycythemia rubra vera.
28
17
The focus of such studies differed from ours: namely, they sought to address the
degree to which variation in PV altered the accuracy of the diagnosis of
polycythemia, whilst we assessed the influence of variation in tHb-mass and PV
on [Hb] per se and on the diagnosis of anemia. Nor have any studies in this field
been comprehensive across disease states, or assessed tHb-mass (rather than
RCV). Nonetheless RCV (by
51
Cr labeling) has been shown to be similar in
anemic and non-anemic CHF patients, suggesting that PV expansion accounted
for this diagnosis.
15
Indeed, this has been shown to occur (using I131-labeled
albumin) in CHF due to systolic dysfunction, with poor correlation between [Hb]
and RCV.
29
Likewise, and using the same technique, Miller showed 19 of 32
patients hospitalized with decompensated CHF to be anemic, with only 4 of these
having a true reduction in RCV.
30
Using the carbon monoxide rebreathing
method, we extend such observations (see Table 2). Overall, 39 of the 109
participants were anemic, in only 2 (13.3%) of whom was this due to a reduced
tHb-mass [352 g and 449 g] in the context of a normal PV. In the remaining
86.7%, reduced [Hb] was accounted for by PV expansion (n= 4 mild to moderate,
tHb-mass 494 ± 76 g, and n= 8 severe, tHb-mass 539 ± 105 g). Interestingly, 14
of the 39 anemic patients (93%) had a relatively raised tHb-mass, with PV
elevated to a greater degree (n= 1 mild to moderate PV expansion (tHb-mass 610
g), n= 13 severe PV expansion (tHb-mass 758 ± 220 g).
The overall prevalence of anemia for our study participants (36%) is similar to
that reported in previous studies in non-cardiac surgical patients (30.4%). 9 Nine
per cent of IBD patients suffered anemia, which is less than has been reported
across European Countries (24%). 12 Some 54% of CHF patients suffered anemia
18
in the current study, somewhat more than has been previously reported in the
Study of Anemia in a Heart Failure Population (STAMINA-HFP) Registry
(34%),
31
or in patients with advanced HF (30%), 32 but in keeping with the data
of others (55.6% 33 to 61%).
34
Of CLD patients, 94% suffered anemia- a figure
somewhat higher that that previously reported by some (50-75%),
keeping with data in decompensated CLD (86%)
37
35,36
but in
or hepatitis C infection
(75%). 38
Amongst healthy volunteers, five (24% of healthy volunteers) were anemic- a
figure in keeping with global data relating to non-pregnant females (30%), 2 and
only slightly higher than the 16% reported in non-pregnant women aged 15-49
years from high income regions and 22% in menstruating women from central
and eastern Europe.
39
This may be related to volunteering bias in the current
study whereby those who thought they might be anemic preferentially applied to
participate.
This study utilized the optimized carbon monoxide rebreathing method, validated
against 51Chromuim radiolabelling methodologies.
40
An advantage of our study
was its assessment of diverse patient groups. Sample sizes, whilst small, were
appropriately powered to explore the relationship between tHb-mass and [Hb]albeit that, for administrative reasons, the sample size for patients with CLD (n=
16) was below the 21 we originally sought, based on the study by Hinrichs and
colleagues.
23
Nonetheless, we were yet able to demonstrate that PV changes in
this group do influence assessed [Hb] and anemia diagnoses.
19
Differing blood sample methods (capillary and venous) yield identical ∆%COHb
(and thus tHb-mass) values.
than that in venous blood.
41
However, capillary [Hb] can be marginally higher
42-45
The use of differing sampling techniques across
testing sites may thus have contributed a little to variation in measured [Hb],
although capillary blood [Hb] values were all corrected to venous conditions, and
all blood samples were collected from the same anatomical site, and with patients
in the same posture (seated). This factor does not therefore weaken the
significance of our findings. Whilst the use of different blood gas machines and
testing staff may have introduced error in the measurement of tHb-mass, we
found a typical error (TE) of repeat tHb-mass measurements of 1.93% (95% CI
1.3-3.4%: unpublished data), values in keeping with other institutions using the
oCOR method. 19, 46
Finally, the oCOR method is quick and simple, avoids the technical difficulties of
working with radiolabelled compounds, 40 offers a minimal burden for patients, is
minimally invasive and is safe even in patients with serious medical conditions
and comorbidities such as stable coronary artery disease.
47
This greatly widens
the applicability of the oCOR test to measure tHb-mass and plasma volume in the
clinical setting. To date, its clinical experimental application has been sparse(e.g. to demonstrate that low tHb-mass may account for impaired exertional
performance in otherwise healthy diabetics.
48
Whilst (rarely yet) applied to the
measurement of red cell mass in patients with polycythemia rubra vera,
28
it has
yet to be utilized in routine clinical practice but might find great value, for
example in the estimation of red cell mass and plasma volume in cases of
presumed excessive erythrocytosis. Our data might support wider use.
20
In conclusion, measured [Hb], and the diagnosis of anemia, can be strongly
influenced by (or can largely depend upon) changes in plasma volume. The scale
of this impact may be greater in some diseases than others. Constraining
investigation of anemia to the identification of causes of reduced Hb synthesis or
of erythrocyte loss or destruction may be inappropriate for many. The concept of
‘anemia’ may thus need refining in clinical practice, and the oCOR method may
support better and more appropriate assessments of the factors influencing
circulating [Hb].
21
Declaration of interests
MG serves on the Medical Advisory Board of Sphere Medical Ltd. MG has
received honoraria for speaking and/or travel expenses from Cortex GmBH (2008
& 2009).
WS is a managing partner of the company "Blood tec GmbH", who provided the
required equipment and expertise during this study for the measurement of
haemoglobin mass using the optimized carbon monoxide rebreathing method.
HEM consults for Deepmind Health on health technology, and is on the Council
of the UK Intensive Care Society but is unaware of any direct or indirect conflict
of interest with the contents of this paper or its related fields.
TR is director of theironclinic.com, and has received speaker fees, honoraria and
research funding from companies including Gideon Richter, Vifor Pharma Ltd
and Pharmocosmos, for work related to anemia, blood transfusion and iron
therapy. He is a board member of the Network for Advancement of Patient Blood
Management, Haemostasis and Thrombosis (NATA).
JMO received an Impact PhD Studentship part funded by University College
London (UCL) and Vifor Pharma Ltd. This funding covered the timespan from
February 2013 to January 2016 and totaled £32,534. JOMP received £9734.06
from the NIHR research management committee academic clinical fellow
research project funding for this study. He was funded by the NIHR ACF
programme for the duration of this study.
22
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29
Tables
Table 1. Hematological variables in anemic and non-anemic participants.
Variable
Anemic (n= 39)
Non-anemic (n= 70)
P-value
. -1
109.6 ± 12.5
138.9 ± 10.6
< 0.0001
[Hb] (g l )
Hct (%)
35.0 ± 5.9
42.4 ± 3.0
< 0.0001
tHb-mass (g)
594 ± 192
711 ± 162
0.001
.
-1
7.7 ± 1.9
9.0 ± 1.8
0.001
tHb-mass (g kg )
BV (ml)
5978 ± 1837
5606 ± 1146
0.257
77.3 ± 16.7
71.6 ± 14.8
0.066
BV (ml.kg-1)
PV (ml)
4083 ± 1351
3434 ± 686
0.007
.
-1
52.6 ± 12.1
44.0 ± 9.6
< 0.0001
PV (ml kg )
PV (%)
68%
61%
< 0.0001
RCV (ml)
1894 ± 692
2171 ± 501
0.018
.
-1
24.7 ± 7.1
27.5 ± 5.7
0.023
RCV (ml kg )
MCV (fl)
88.0 ± 6.2
91.0 ± 6.6
0.038
MCH (pg)
29.3 ± 2.9
30.1 ± 2.2
0.218
. -1
333.1 ± 18.0
330.5 ± 12.2
0.477
MCHC (g l )
RDW (%)
14.5 ± 1.7
13.7 ± 1.1
0.024
. -1
114.9 ± 117.4
84.3 ± 58.2
0.166
Creatinine (μmol l )
. -1
Albumin (g l )
37.4 ± 8.7
43.7 ± 4.9
0.001
[Hb], Hemoglobin concentration; Hct, hematocrit; tHb-mass, total hemoglobin mass;
BV, blood volume; PV, plasma volume; RCV, red cell volume; MCV, mean
corpuscular volume; MCH, mean corpuscular hemoglobin; MCHC, mean
corpuscular hemoglobin concentration; RDW, red cell distribution width. Anemia
defined according to World Health Organization criteria ([Hb] <130 g.l-1 in men and
<120 g.l-1 in women. Data are presented as mean ± SD, or frequency (%).
30
Table 2. Anemia classification based on hemoglobin concentration, red cell volume and plasma volume in all patients (n= 109).
Anemia status
Normal PV
Mild to moderate PV
Severe PV
PV
Total
expansion
expansion
contraction
Non anemic
Normal RCV
12
8
1
1
22
RCV deficit
4
1
0
2
7
RCV excess
5
17
19
0
41
Total
21
26
20
3
70
Anemic
Normal RCV
1
5
5
0
11
RCV deficit
2
4
8
0
15
RCV excess
0
1
13
0
14
Total
3
10
26
0
39
Normal BV, PV and RCV were classified as derived volumes from measured tHb-mass within ± 8% of the expected normal volumes on an
individual level. Mild to moderate volume expansion was considered >8% to <25% deviation from expected norms, and severe as >25% of the
expected normal volume. BV, blood volume, PV, plasma volume, RCV, red cell volume. Anemia defined according to World Health
Organization criteria ([Hb] <130 g.l-1 in men and <120 g.l-1 in women. Values are expressed as counts
31
Figure legends
Figure 1. Hematological variables in healthy volunteers and patient sub-groups.
Hct (%), hematocrit percentage (A); [Hb], hemoglobin concentration (B); tHbmass, total hemoglobin mass (g & g.kg-1) (C & D). HV, healthy volunteers; IBD,
inflammatory bowel disease; HF, heart failure; LD, liver disease. *p< 0.0001 for
Hct and [Hb] in LD patients compared to all other groups. No differences in tHbmass (g or g.kg-1) between groups. Data expressed as mean (± standard deviation
error bars).
Figure 2. Plasma volume in healthy volunteers and patient sub-groups. Plasma
volume (ml & ml.kg-1) (A & B). HV, healthy volunteers; IBD, inflammatory
bowel disease; HF, heart failure; LD, liver disease; PV, plasma volume. (A) PV
(ml) between LD and HV, *p= 0.006, PV (ml) between LD and IBD, **p= 0.002
and PV (ml) between LD and surgical patients, †p= 0.003; (B) PV (ml kg-1)
between LD and IBD, *p= 0.008, PV between LD and surgical patients, **p=
0.004. Data expressed as mean (± standard deviation error bars).
Figure 3. Unadjusted relationship between hemoglobin concentration and total
hemoglobin mass. Healthy controls (A, n= 21), patients with IBD (B, n= 22),
surgical patients (C, n= 28), liver disease (D, n= 16) and HF (E, n= 22). tHb-mass
(g), total hemoglobin mass; [Hb] (g.l-1), hemoglobin concentration; IBD,
inflammatory bowel disease; HF, heart failure.
Figure 4. Hemoglobin concentration and hematocrit in all patients categorized by
plasma volume status. Plasma volume contraction (n= 3) was classified as >
minus 8% from expected norms. Normal PV (n= 24) was classified as derived PV
within ± 8% of the expected normal volume on an individual level. Mild to
moderate volume expansion (n= 36) was considered >8% to <25% deviation from
expected norms, and severe PV expansion (n= 46) as >25% of the expected
normal volume. *p= 0.005 for [Hb] in severe PV expansion vs. mild to moderate,
†p< 0.0001 for [Hb] in severe PV expansion vs. normal PV. PV, plasma volume;
[Hb], hemoglobin concentration (g.l-1); Hct (%), hematocrit percentage. Data
expressed as mean (± standard deviation error bars).
Figure 5. Individual participant data for total hemoglobin mass, plasma volume
and hemoglobin concentration. Participants ranked by tHb-mass (g.kg-1) (dark
grey bars) from smallest to largest with corresponding PV (ml.kg-1) (light grey
bars) and [Hb] (g.l-1) (black circles) in healthy volunteers (A), inflammatory
bowel disease (B), surgical (C), chronic heart failure (D), and chronic liver
disease (E). tHb-mass, total hemoglobin mass; PV, plasma volume; [Hb],
hemoglobin concentration.
32
Supplementary Information
Supplemental Methods: Participant recruitment and testing sites, eligibility criteria, blood
sampling, calculation of total haemoglobin mass and normal plasma volumes
Table S1: Surgical specialty for planned surgical procedure
Table S2: Characteristics and aetiology of inflammatory bowel disease patients
Table S3: Characteristics, medications and aetiology of liver disease patients.
Table S4: Characteristics, medications and aetiology of chronic heart failure patients.
Table S5: Relationship between total haemoglobin mass and haemoglobin concentration
in sub-groups based on plasma volume status.
Participant recruitment and testing sites
Patients were recruited from those managed at University College Hospital (University
College London Hospitals NHS Foundation Trust, UCLH), Southampton General
Hospital (University Hospital Southampton NHS Foundation Trust) and the Royal Free
Hospital (Royal Free London NHS Foundation Trust, RFH). Supplementary Figure 1
shows a Consolidated Standards of Reporting Trials (CONSORT)- style flow diagram
indicating included and excluded patients and specific sub-groups. HV, patients with
IBD and those awaiting surgery were recruited from and tested at UCLH only. Patients
with CLD were recruited from and tested at all three sites, and those with CHF at UCLH
and Southampton. Healthy volunteers were members of staff at UCLH or University
College London (UCL) recruited by word of mouth or email advertisement. Patients
were identified and recruited at outpatient clinics or when attending other routine clinical
appointments.
Eligibility criteria
Inclusion criteria for all participants were, age >18 years, and ability give informed
consent and to comply with basic breath-holding instructions. Healthy volunteers were
additionally free from known chronic disease or use of regular medications. In CHF
(clinically diagnosed and under treatment, confirmed- as clinically indicated- by the
presence of a circulating concentration of B-type natriuretic peptide (BNP) >200 pg ml1
), additional inclusion criteria were echocardiographic or cardiac magnetic resonance
imaging (cMRI) evidence of left ventricular (LV) systolic impairment as defined by a left
ventricular ejection fraction of less than 50%; New York Heart Association (NYHA)
class II-IV; and not fully stabilised, i.e. still symptomatic with shortness of breath and/or
peripheral oedema and/or clinical signs of bibasal crepitations or peripheral oedema.
Patients with CLD all had a diagnosis of alcoholic liver disease, primary sclerosing
cholangitis, hepatitis C or cryptogenic cirrhosis. A confirmed diagnosis of IBD (either
Crohn’s disease or ulcerative colitis) was required for inclusion into this group. For
surgical patients, inclusion was based on a patient being scheduled to undergo elective
major surgery, regardless of specialty.
Excluded were prisoners, or those with a baseline %COHb greater than 5% (as can occur
in smokers), presence of haemoglobinopathy.
Blood sampling
At UCLH and RFH, [Hb] was determined from a fingertip capillary blood sample (Hb
201 Microvette, Hemocue AB, Angelholm, Sweden), analysed immediately (HemoCue®
Hb 201+, Hemocue AB, Angelholm, Sweden) when [Hb] could not be obtained from
venous blood at the time of testing or was not available on the same day as tHb-mass
measurement from hospital electronic records. At UCLH and RFH, fingertip capillary
samples (200 µl) were collected before and 6- and 8-min after the start of CO rebreathing
(Na-heparinized 200 µl RAPIDLyte Multicap Capillary tubes, Siemens Healthcare
Diagnostics Inc, Deerfield, USA), with samples analysed within 15 minutes for percent
carboxyhaemoglobin (%COHb) using a blood gas analyser (Hemoximeter; Cobas b 221
POC system, Roche Diagnostics Ltd, Switzerland). At Southampton, [Hb] was measured
in venous blood. An intravenous cannula was inserted prior to tHb-mass testing at
Southampton, allowing venous blood samples (200 µl) to be collected before and at 6and 8-mins after CO rebreathing via a Na-heparinized blood gas syringe (RAPIDLyte,
Siemens Healthcare Diagnostics Inc, Deerfield, USA). %COHb was determined at
Southampton using the RAPIDPoint 500 Blood Gas System (Siemens Healthcare
Diagnostics Inc, Deerfield, USA). All blood samples for the determination of [Hb],
haematocrit (Hct) and %COHb were collected under the same conditions, from the same
anatomical site, and with patients in a seated position. Blood samples were analysed
within 10-15 minutes of one another due to %COHb being analysed after the oCOR test
using a blood gas machine (which takes 15 minutes). Blood sampling from venous,
arterial and capillary blood yields an identical ∆%COHb and therefore identical tHbmass values. 1
Calculation of tHb-mass
tHb-mass was calculated using a specifically design excel spreadsheet (Microsoft Excel
2011 for Apple Macintosh) using the formula:
tHb-mass (g) = K x MCO(ml) x 100 x (Δ%COHb x 1.39)-1
K = barometric pressure x 760-1 x [1(0.003661 x temperature)]
MCO = COadm – (COsystem + lung (after disconnection) + COexhaled (after disconnection)
COadm = CO volume administered into the system
COsystem
+ lung (after disconnection)
= CO concentration in spirometer x (spirometer volume +
remaining volume in the lung after disconnection)
COexhaled (after disconnection) = end-tidal CO concentration x alveolar ventilation x time
Δ%COHb = difference between baseline %COHb and %COHb post CO administration
(average of 6- and 8-min %COHb values)
1.39 = Hufners number (constant) (ml CO x g Hb-1)
where:
lung residual volume, 1500 ml in men, 1200 ml in women; alveolar ventilation, 5000 ml
min-1, CO concentration is in parts per million (ppm)
Blood volume (BV), plasma volume (PV) and red cell volume (RCV) were calculated
from mean corpuscular haemoglobin concentration (MCHC), [Hb] and tHb-mass, as
below:
BV (ml) = tHb-mass (g)/[Hb] (g.dl-1) • 100
RCV (ml) = tHb-mass (g)/MCHC • 100
PV (ml) = BV – RCV
When Hct and [Hb] values were obtained from capillary blood at UCLH and the RFH
these values were corrected to venous conditions using the following formulas 2, 3:
[Hb] (g.dl-1) = [Hbcapillary] • 0.8787 + 1.24
Hct (%) = [Hctcapillary] • 0.8425 + 5.23
Estimation of normal adult values for PV were calculated using the formulas from the
1995 Expert Panel on Radionuclides of the International Council for Standardisation in
Haematology. 4
Equation 1. Estimation of normal male plasma volume
Mean normal PV (ml) = 1578 x S
Equation 2. Estimation of normal female adult plasma volume
Mean normal PV (ml) = 1395 x S
Where S = body surface area (m2) calculated using the formula of Du Bois and Du Bois.
5
PV values were adjusted for age, sex, weight, and height using a published formula to
calculate normal volumes as derived from >100,000 measurements of height and weight
from Metropolitan Life tables. 6 Normal PV was classified as measured volumes within ±
8% of the expected normal volume on an individual level. Mild to moderate volume
expansion was considered >8% to ≤25% positive deviation from expected norms, and
severe as >25% above the expected normal volume. 6
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Haemoglobin mass in cyclists during stage racing. Int J Sports Med. 2008;29(5):372-378.
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5.
Du Bois D, Du Bois E. Clinical calorimetry: Tenth paper to estimate the
approximate surface area if height and weight are known. Arch Intern Med. 1916;17:863871.
6.
Feldschuh J, Enson Y. Prediction of the normal blood volume. Relation of blood
volume to body habitus. Circulation. 1977;56(4 Pt 1):605-612.
Eligible patients
approached for
inclusion n= 499
Excluded
n=390
Healthy volunteers
n= 21
Patients included
for analysis
n= 109
Chronic liver disease
n= 16
Inflammatory bowel disease
n= 22
Chronic heart failure
n= 21
Surgical
n= 28
Supplementary Figure 1. Consolidated Standards of Reporting Trials (CONSORT)- style
flow diagram indicating included and excluded patients and specific sub-groups. Excluded
patients are those who declined participation, failed to respond to correspondence via letter
and telephone contact or could not be contacted despite multiple attempts by the research
team.
Table-S1. Surgical specialty for planned surgical procedure (n= 28).
Surgical specialty
Frequency N (%)
8 (28.5%)
Upper gastrointestinal
8 (28.5%)
Lower gastrointestinal
7 (25%)
Orthopaedic
3 (10.7%)
Other
2 (7.1%)
Urology
Table-S2. Characteristics and aetiology of inflammatory bowel disease patients.
Variable
IBD (n= 22)
Gender
Male (%)
50%
Age (yr)
50 (33-62)
Height (cm)
170.2 ± 7.3
Weight (kg)
77.7 ± 18.1
Aetiology of IBD
Crohn’s disease
4 (18%)
Small bowel CD
2 (9%)
Terminal ileal CD
1 (4.5%
Ulcerative colitis
9 (41%)
Ulcerative proctitis
3 (14%)
Pan UC
2 (9%)
Collagenous colitis
1 (4.5%)
IBD, Inflammatory bowel disease; CD, Crohn’s disease; UC, Ulcerative colitis
Table-S3. Characteristics, medications and aetiology of liver disease patients.
Variable
LD (n= 16)
Gender
Male (%)
75%
Age (yr)
51 (48-55)
Height (cm)
174.8 ± 8.9
Weight (kg)
85.3 ± 18.5
Primary aetiology of liver disease
Hepatitis
3 (19%)
ALD
8 (50%)
Cryptogenic cirrhosis
2 (12%)
Sclerosing cholangitis
2 (12%)
Other
1 (6%)
Hypertension
1 (6%)
Medication
Beta blocker
3 (19%)
ACE inhibitor
0 (0%)
Statin
0 (0%)
Diuretic
5 (31%)
Diuretic times per day
None
11 (69 %)
Once
5 (31 %)
Bi daily
0
ALD, decompensated alcoholic liver disease; ACE inhibitor, angiotensin-converting-enzyme
inhibitor.
Table-S4. Characteristics, medications and aetiology of chronic heart failure patients.
Variable
CHF (n= 22)
Gender
Male (%)
82%
Age (yr)
68 (61-75)
Height (cm)
173.5 ± 8.1
Weight (kg)
80.4 ± 15.9
Aetiology of heart failure
Ischaemic heart disease
7 (32%)
Cardiomyopathy
10 (45%)
Ischaemic
5 (22%)
Non-ischaemic
5 (22%)
Other
5 (22%)
Hypertension
7 (32%)
NHYA class
I
2 (9%)
II
14 (64%)
III
4 (18%)
IV
2 (9%)
LVEF (%)
33.2 ± 11.4
Medication
Beta blocker
19 (86%)
ACE inhibitor
20 (91%)
Statin
16 (73%)
Diuretic
17 (77%)
Diuretic dose (mg)
25 ± 29
Diuretic times per day
None
5 (22%)
Once
14 (64%)
Bi daily
3 (14 %)
NYHA, New York Heart Association Class; LVEF (%), left ventricular ejection fraction;
ACE inhibitor, angiotensin-converting-enzyme inhibitor
Table-S5. Relationship between total haemoglobin mass and haemoglobin concentration in
sub-groups based on plasma volume status.
Plasma volume status
Sub group
Normal
Mild to moderate
Severe
IBD
(n= 9)
(n= 7)
(n= 5)
r= 0.86, p= 0.003
r= 0.94, p< 0.002
r= 0.78, p= 0.118
Surgical
(n= 8)
(n= 14)
(n= 5)
r= 0.94, p= 0.001
n= 0.78, p= 0.001
r= 0.80, p= 0.104
CHF
(n= 4)
(n= 6)
(n= 11)
r= 0.95, p= 0.046
r= 0.86, p< 0.029
r= 0.59, p= 0.055
HV
(n=2)
(n= 8)
(n= 11)
r= 0.91, p< 0.002
r= 0.89, p< 0.0001
r, Pearson’s correlation coefficient; PV values were adjusted for age, sex, weight, and height
using a published formula to calculate normal volumes as derived from >100,000
measurements of height and weight from Metropolitan Life tables. 6 Normal PV was
classified as measured volumes within ± 8% of the expected normal volume on an individual
level. Mild to moderate volume expansion was considered >8% to <25% deviation from
expected norms, and severe as >25% of the expected normal volume. 6 Insufficient numbers
to perform sub-group analysis in chronic liver disease group. IBD, inflammatory bowel
disease; CHF, chronic heart failure; HV, healthy volunteers.